Climate security and a vulnerability model for conflict prevention: a systematic literature review focusing on African agriculture

Sustainable Earth

article

Pearson, Daniel¹  Newman, Peter¹ 

[1] Curtin University Sustainability Policy Institute (CUSP)

关键词: Climate change;    Adaptation;    Violent conflict;    Vulnerability;   

DOI  :  10.1186/s42055-019-0009-6

学科分类：过敏症与临床免疫学

来源: Springer

【 摘 要 】

Climate change poses credible threats to the livelihoods of many. This paper addresses how climate change adaptation can help counter the increased risk of violent conflict that is associated with these climatic changes. Extant climate-conflict links however, involve a complex interaction of many factors that mediate the impact of climate change. Thus, adaptation methods should not focus simply on the direct impacts of these changes. This paper, using the Systematic Literature Review method, conducts an analysis of the climate-conflict and climate adaptation literature covering 46 papers, with a geographical restriction of Africa and focusing on the quantitative comparative literature. This SLR had two key aims, first to understand how links and common areas of understanding between the climate-conflict and climate adaptation fields of research could inform future empirical quantitative research into the notion of climate adaptation as conflict prevention. And secondly, how future quantitative comparative climate conflict research could be informed. It suggests a Vulnerability Model that assists in understanding how vulnerability, understood through the lens of exposure, sensitivity and adaptive capacity, can provide researchers and policy makers with the various factors, both direct and indirect, which can identify where violent conflict might occur. Simultaneously, it illustrates what factors influence the adaptation needs of an agricultural community and hence how adaptation could reduce the risk of future violent conflict. Future quantitative comparative climate-conflict research could also benefit by using disaggregated sub-national data, focusing on agricultural communities using variables that draw on the Vulnerability Model.

【 授权许可】

CC BY